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library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.1.2
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## v tibble 3.1.6 v dplyr 1.0.8
## v tidyr 1.2.0 v stringr 1.4.0
## v readr 2.1.2 v forcats 0.5.1
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library(ggplot2)
library(plotly)
## Warning: package 'plotly' was built under R version 4.1.3
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
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## filter
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##
## layout
(df <- read_csv(here::here("Results", 'Seaon Total Innings.csv')))
## Rows: 150292 Columns: 7
## -- Column specification --------------------------------------------------------
## Delimiter: ","
## dbl (7): Inning, Home Team, First, Second, Third, Outs, Inning Runs
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 150,292 x 7
## Inning `Home Team` First Second Third Outs `Inning Runs`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 0 0 0 0 0 0
## 2 1 0 0 0 0 1 0
## 3 1 0 1 0 0 2 0
## 4 1 1 0 0 0 0 0
## 5 1 1 0 0 0 1 0
## 6 1 1 0 0 0 2 0
## 7 2 0 0 0 0 0 1
## 8 2 0 0 0 0 1 1
## 9 2 0 0 0 1 1 1
## 10 2 0 0 1 0 1 1
## # ... with 150,282 more rows
df <- df %>%
mutate(`Scored` = if_else(`Inning Runs` >= 1,TRUE,FALSE))
df_group <- df %>%
group_by(First, Second, Third, Outs) %>%
summarise(Runs = sum(`Inning Runs`),
Occurences = n(),
`Probabilty of Scoring` = mean(Scored))
## `summarise()` has grouped output by 'First', 'Second', 'Third'. You can
## override using the `.groups` argument.
df_group <- df_group %>%
mutate(`Runs Expected` = Runs/Occurences) %>%
unite(Onbase, First:Third)
runs_expected_matrix <- df_group %>%
pivot_wider(id_cols=Onbase, names_from=Outs, values_from=`Runs Expected`, names_prefix='Outs: ', names_sep=' ') %>%
arrange(desc('Outs: 0'))
run_prob_matrix <- df_group %>%
pivot_wider(id_cols=Onbase, names_from=Outs, values_from=`Probabilty of Scoring`, names_prefix='Outs: ', names_sep=' ')
View(df_group)
View(runs_expected_matrix)
View(run_prob_matrix)
ggplot(df_group, aes(x=Onbase, y=`Runs Expected`))+
geom_boxplot()

ggplot(df_group, aes(y=Onbase, fill=`Runs Expected`, x=Outs))+
geom_tile()

p <- df_group %>%
ggplot(aes(y=Onbase, fill=`Probabilty of Scoring`, x=Outs))+
geom_tile()
ggplotly(p)
```r
df_bases <- df %>%
unite(Onbase, First:Third) %>%
mutate(Outs = as.factor(Outs))
p <- df_bases %>%
ggplot(aes(x=`Inning Runs`, color=Outs))+
geom_density()
ggplotly(p)